Mohammad Emtiyaz Khan

114 papers A* 26A 9B 1C 3Journal 67Unranked 7

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	A Stein Identity for q-Gaussians with Bounded Support. CoRR Sophia Sklaviadis, Thomas Möllenhoff, André F. T. Martins, Mário A. T. Figueiredo, Mohammad Emtiyaz Khan
2026	J	`jnl`	Variational Visual Question Answering for Uncertainty-Aware Selective Prediction. Trans. Mach. Learn. Res. Tobias Jan Wieczorek, Nathalie Daun, Mohammad Emtiyaz Khan, Marcus Rohrbach
2025	J	`jnl`	Compact Memory for Continual Logistic Regression. CoRR Yohan Jung, Hyungi Lee, Wenlong Chen, Thomas Möllenhoff, Yingzhen Li, Juho Lee, Mohammad Emtiyaz Khan
2025	A*	`conf`	Connecting Federated ADMM to Bayes. ICLR Siddharth Swaroop, Mohammad Emtiyaz Khan, Finale Doshi-Velez
2025	J	`jnl`	Connecting Federated ADMM to Bayes. CoRR Siddharth Swaroop, Mohammad Emtiyaz Khan, Finale Doshi-Velez
2025	J	`jnl`	Federated ADMM from Bayesian Duality. CoRR Thomas Möllenhoff, Siddharth Swaroop, Finale Doshi-Velez, Mohammad Emtiyaz Khan
2025	J	`jnl`	Improving LoRA with Variational Learning. CoRR Bai Cong, Nico Daheim, Yuesong Shen, Rio Yokota, Mohammad Emtiyaz Khan, Thomas Möllenhoff
2025	J	`jnl`	Information Geometry of Variational Bayes. CoRR Mohammad Emtiyaz Khan
2025	A	`ed.`	International Conference on Artificial Intelligence and Statistics, AISTATS 2025, Mai Khao, Thailand, 3-5 May 2025. AISTATS Yingzhen Li, Stephan Mandt, Shipra Agrawal, Mohammad Emtiyaz Khan
2025	J	`jnl`	Knowledge Adaptation as Posterior Correction. CoRR Mohammad Emtiyaz Khan
2025	J	`jnl`	Log-Normal Multiplicative Dynamics for Stable Low-Precision Training of Large Networks. CoRR Keigo Nishida, Eren Mehmet Kiral, Kenichi Bannai, Mohammad Emtiyaz Khan, Thomas Möllenhoff
2025	J	`jnl`	Natural Variational Annealing for Multimodal Optimization. CoRR Tâm Le Minh, Julyan Arbel, Thomas Möllenhoff, Mohammad Emtiyaz Khan, Florence Forbes
2025	J	`jnl`	Optimization Guarantees for Square-Root Natural-Gradient Variational Inference. CoRR Navish Kumar, Thomas Möllenhoff, Mohammad Emtiyaz Khan, Aurélien Lucchi
2025	J	`jnl`	Optimization Guarantees for Square-Root Natural-Gradient Variational Inference. Trans. Mach. Learn. Res. Navish Kumar, Thomas Möllenhoff, Mohammad Emtiyaz Khan, Aurélien Lucchi
2025	J	`jnl`	SVRG and Beyond via Posterior Correction. CoRR Nico Daheim, Thomas Möllenhoff, Ming Liang Ang, Mohammad Emtiyaz Khan
2025	J	`jnl`	Variational Learning Finds Flatter Solutions at the Edge of Stability. CoRR Avrajit Ghosh, Bai Cong, Rio Yokota, Saiprasad Ravishankar, Rongrong Wang, Molei Tao, Mohammad Emtiyaz Khan, Thomas Möllenhoff
2025	J	`jnl`	Variational Learning Induces Adaptive Label Smoothing. CoRR Sin-Han Yang, Zhedong Liu, Gian Maria Marconi, Mohammad Emtiyaz Khan
2025	J	`jnl`	Variational Visual Question Answering. CoRR Tobias Jan Wieczorek, Nathalie Daun, Mohammad Emtiyaz Khan, Marcus Rohrbach
2024	J	`jnl`	AI for Social Good (Dagstuhl Seminar 24082). Dagstuhl Reports Claudia Clopath, Ruben De Winne, Mohammad Emtiyaz Khan, Jacopo Margutti
2024	A*	`conf`	Conformal Prediction via Regression-as-Classification. ICLR Etash Kumar Guha, Shlok Natarajan, Thomas Möllenhoff, Mohammad Emtiyaz Khan, Eugène Ndiaye
2024	J	`jnl`	Conformal Prediction via Regression-as-Classification. CoRR Etash Kumar Guha, Shlok Natarajan, Thomas Möllenhoff, Mohammad Emtiyaz Khan, Eugène Ndiaye
2024	J	`jnl`	How to Weight Multitask Finetuning? Fast Previews via Bayesian Model-Merging. CoRR Hugo Monzón Maldonado, Thomas Möllenhoff, Nico Daheim, Iryna Gurevych, Mohammad Emtiyaz Khan
2024	A*	`conf`	Model Merging by Uncertainty-Based Gradient Matching. ICLR Nico Daheim, Thomas Möllenhoff, Edoardo M. Ponti, Iryna Gurevych, Mohammad Emtiyaz Khan
2024	J	`jnl`	Position Paper: Bayesian Deep Learning in the Age of Large-Scale AI. CoRR Theodore Papamarkou, Maria Skoularidou, Konstantina Palla, Laurence Aitchison, Julyan Arbel, David B. Dunson, Maurizio Filippone, Vincent Fortuin, Philipp Hennig, José Miguel Hernández-Lobato, Aliaksandr Hubin, Alexander Immer, Theofanis Karaletsos, Mohammad Emtiyaz Khan, Agustinus Kristiadi, Yingzhen Li, Stephan Mandt, Christopher Nemeth, Michael A. Osborne, Tim G. J. Rudner, David Rügamer, Yee Whye Teh, Max Welling, Andrew Gordon Wilson, Ruqi Zhang
2024	A*	`conf`	Position: Bayesian Deep Learning is Needed in the Age of Large-Scale AI. ICML Theodore Papamarkou, Maria Skoularidou, Konstantina Palla, Laurence Aitchison, Julyan Arbel, David B. Dunson, Maurizio Filippone, Vincent Fortuin, Philipp Hennig, José Miguel Hernández-Lobato, Aliaksandr Hubin, Alexander Immer, Theofanis Karaletsos, Mohammad Emtiyaz Khan, Agustinus Kristiadi, Yingzhen Li, Stephan Mandt, Christopher Nemeth, Michael A. Osborne, Tim G. J. Rudner, David Rügamer, Yee Whye Teh, Max Welling, Andrew Gordon Wilson, Ruqi Zhang
2024	J	`jnl`	Rethinking the Role of Bayesianism in the Age of Modern AI (Dagstuhl Seminar 24461). Dagstuhl Reports Vincent Fortuin, Mohammad Emtiyaz Khan, Mark van der Wilk, Zoubin Ghahramani, Katharine Fisher
2024	A*	`conf`	Variational Learning is Effective for Large Deep Networks. ICML Yuesong Shen, Nico Daheim, Bai Cong, Peter Nickl, Gian Maria Marconi, Clement Bazan, Rio Yokota, Iryna Gurevych, Daniel Cremers, Mohammad Emtiyaz Khan, Thomas Möllenhoff
2024	J	`jnl`	Variational Learning is Effective for Large Deep Networks. CoRR Yuesong Shen, Nico Daheim, Bai Cong, Peter Nickl, Gian Maria Marconi, Clement Bazan, Rio Yokota, Iryna Gurevych, Daniel Cremers, Mohammad Emtiyaz Khan, Thomas Möllenhoff
2024	J	`jnl`	Variational Low-Rank Adaptation Using IVON. CoRR Bai Cong, Nico Daheim, Yuesong Shen, Daniel Cremers, Rio Yokota, Mohammad Emtiyaz Khan, Thomas Möllenhoff
2023	J	`jnl`	Bridging the Gap Between Target Networks and Functional Regularization. Trans. Mach. Learn. Res. Alexandre Piché, Valentin Thomas, Joseph Marino, Rafael Pardinas, Gian Maria Marconi, Christopher Pal, Mohammad Emtiyaz Khan
2023	A	`conf`	Exploiting Inferential Structure in Neural Processes. UAI Dharmesh Tailor, Mohammad Emtiyaz Khan, Eric T. Nalisnick
2023	J	`jnl`	Exploiting Inferential Structure in Neural Processes. CoRR Dharmesh Tailor, Mohammad Emtiyaz Khan, Eric T. Nalisnick
2023	J	`jnl`	Improving Continual Learning by Accurate Gradient Reconstructions of the Past. Trans. Mach. Learn. Res. Erik A. Daxberger, Siddharth Swaroop, Kazuki Osawa, Rio Yokota, Richard E. Turner, José Miguel Hernández-Lobato, Mohammad Emtiyaz Khan
2023	A*	`conf`	Memory-Based Dual Gaussian Processes for Sequential Learning. ICML Paul Edmund Chang, Prakhar Verma, S. T. John, Arno Solin, Mohammad Emtiyaz Khan
2023	J	`jnl`	Memory-Based Dual Gaussian Processes for Sequential Learning. CoRR Paul E. Chang, Prakhar Verma, S. T. John, Arno Solin, Mohammad Emtiyaz Khan
2023	J	`jnl`	Model Merging by Uncertainty-Based Gradient Matching. CoRR Nico Daheim, Thomas Möllenhoff, Edoardo Maria Ponti, Iryna Gurevych, Mohammad Emtiyaz Khan
2023	—	`ed.`	Proceedings of the 1st ContinualAI Unconference, 9 October 2023, Virtual CLAI Unconf Siddharth Swaroop, Martin Mundt, Rahaf Aljundi, Mohammad Emtiyaz Khan
2023	A*	`conf`	SAM as an Optimal Relaxation of Bayes. ICLR Thomas Möllenhoff, Mohammad Emtiyaz Khan
2023	A*	`conf`	Simplifying Momentum-based Positive-definite Submanifold Optimization with Applications to Deep Learning. ICML Wu Lin, Valentin Duruisseaux, Melvin Leok, Frank Nielsen, Mohammad Emtiyaz Khan, Mark Schmidt
2023	J	`jnl`	Simplifying Momentum-based Riemannian Submanifold Optimization. CoRR Wu Lin, Valentin Duruisseaux, Melvin Leok, Frank Nielsen, Mohammad Emtiyaz Khan, Mark Schmidt
2023	J	`jnl`	The Bayesian Learning Rule. J. Mach. Learn. Res. Mohammad Emtiyaz Khan, Håvard Rue
2023	A	`conf`	The Lie-Group Bayesian Learning Rule. AISTATS Eren Mehmet Kiral, Thomas Möllenhoff, Mohammad Emtiyaz Khan
2023	J	`jnl`	The Lie-Group Bayesian Learning Rule. CoRR Eren Mehmet Kiral, Thomas Möllenhoff, Mohammad Emtiyaz Khan
2023	J	`jnl`	The Memory Perturbation Equation: Understanding Model's Sensitivity to Data. CoRR Peter Nickl, Lu Xu, Dharmesh Tailor, Thomas Möllenhoff, Mohammad Emtiyaz Khan
2023	A*	`conf`	The Memory-Perturbation Equation: Understanding Model's Sensitivity to Data. NeurIPS Peter Nickl, Lu Xu, Dharmesh Tailor, Thomas Möllenhoff, Mohammad Emtiyaz Khan
2023	J	`jnl`	Variational Bayes Made Easy. CoRR Mohammad Emtiyaz Khan
2022	J	`jnl`	Can Calibration Improve Sample Prioritization? CoRR Ganesh Tata, Gautham Krishna Gudur, Gopinath Chennupati, Mohammad Emtiyaz Khan
2022	J	`jnl`	SAM as an Optimal Relaxation of Bayes. CoRR Thomas Möllenhoff, Mohammad Emtiyaz Khan
2021	J	`jnl`	Beyond Target Networks: Improving Deep Q-learning with Functional Regularization. CoRR Alexandre Piché, Joseph Marino, Gian Maria Marconi, Christopher Joseph Pal, Mohammad Emtiyaz Khan
2021	A*	`conf`	Dual Parameterization of Sparse Variational Gaussian Processes. NeurIPS Vincent Adam, Paul E. Chang, Mohammad Emtiyaz Khan, Arno Solin
2021	J	`jnl`	Dual Parameterization of Sparse Variational Gaussian Processes. CoRR Vincent Adam, Paul E. Chang, Mohammad Emtiyaz Khan, Arno Solin
2021	A*	`conf`	Knowledge-Adaptation Priors. NeurIPS Mohammad Emtiyaz Khan, Siddharth Swaroop
2021	J	`jnl`	Knowledge-Adaptation Priors. CoRR Mohammad Emtiyaz Khan, Siddharth Swaroop
2021	A*	`conf`	Scalable Marginal Likelihood Estimation for Model Selection in Deep Learning. ICML Alexander Immer, Matthias Bauer, Vincent Fortuin, Gunnar Rätsch, Mohammad Emtiyaz Khan
2021	J	`jnl`	Scalable Marginal Likelihood Estimation for Model Selection in Deep Learning. CoRR Alexander Immer, Matthias Bauer, Vincent Fortuin, Gunnar Rätsch, Mohammad Emtiyaz Khan
2021	J	`jnl`	Structured second-order methods via natural gradient descent. CoRR Wu Lin, Frank Nielsen, Mohammad Emtiyaz Khan, Mark Schmidt
2021	J	`jnl`	Subset-of-Data Variational Inference for Deep Gaussian-Processes Regression. CoRR Ayush Jain, P. K. Srijith, Mohammad Emtiyaz Khan
2021	A	`conf`	Subset-of-data variational inference for deep Gaussian-processes regression. UAI Ayush Jain, P. K. Srijith, Mohammad Emtiyaz Khan
2021	J	`jnl`	The Bayesian Learning Rule. CoRR Mohammad Emtiyaz Khan, Håvard Rue
2021	J	`jnl`	Tractable structured natural gradient descent using local parameterizations. CoRR Wu Lin, Frank Nielsen, Mohammad Emtiyaz Khan, Mark Schmidt
2021	A*	`conf`	Tractable structured natural-gradient descent using local parameterizations. ICML Wu Lin, Frank Nielsen, Mohammad Emtiyaz Khan, Mark Schmidt
2020	A*	`conf`	Beyond Unfolding: Exact Recovery of Latent Convex Tensor Decomposition Under Reshuffling. AAAI Chao Li, Mohammad Emtiyaz Khan, Zhun Sun, Gang Niu, Bo Han, Shengli Xie, Qibin Zhao
2020	A*	`conf`	Continual Deep Learning by Functional Regularisation of Memorable Past. NeurIPS Pingbo Pan, Siddharth Swaroop, Alexander Immer, Runa Eschenhagen, Richard E. Turner, Mohammad Emtiyaz Khan
2020	J	`jnl`	Continual Deep Learning by Functional Regularisation of Memorable Past. CoRR Pingbo Pan, Siddharth Swaroop, Alexander Immer, Runa Eschenhagen, Richard E. Turner, Mohammad Emtiyaz Khan
2020	—	`conf`	Fast Variational Learning in State-Space Gaussian Process Models. MLSP Paul E. Chang, William J. Wilkinson, Mohammad Emtiyaz Khan, Arno Solin
2020	J	`jnl`	Fast Variational Learning in State-Space Gaussian Process Models. CoRR Paul E. Chang, William J. Wilkinson, Mohammad Emtiyaz Khan, Arno Solin
2020	A*	`conf`	Handling the Positive-Definite Constraint in the Bayesian Learning Rule. ICML Wu Lin, Mark Schmidt, Mohammad Emtiyaz Khan
2020	J	`jnl`	Handling the Positive-Definite Constraint in the Bayesian Learning Rule. CoRR Wu Lin, Mark Schmidt, Mohammad Emtiyaz Khan
2020	A*	`conf`	Training Binary Neural Networks using the Bayesian Learning Rule. ICML Xiangming Meng, Roman Bachmann, Mohammad Emtiyaz Khan
2020	J	`jnl`	Training Binary Neural Networks using the Bayesian Learning Rule. CoRR Xiangming Meng, Roman Bachmann, Mohammad Emtiyaz Khan
2020	A*	`conf`	Variational Imitation Learning with Diverse-quality Demonstrations. ICML Voot Tangkaratt, Bo Han, Mohammad Emtiyaz Khan, Masashi Sugiyama
2019	C	`conf`	A Generalization Bound for Online Variational Inference. ACML Badr-Eddine Chérief-Abdellatif, Pierre Alquier, Mohammad Emtiyaz Khan
2019	J	`jnl`	A Generalization Bound for Online Variational Inference. CoRR Badr-Eddine Chérief-Abdellatif, Pierre Alquier, Mohammad Emtiyaz Khan
2019	J	`jnl`	AI for the Social Good (Dagstuhl Seminar 19082). Dagstuhl Reports Claudia Clopath, Ruben De Winne, Mohammad Emtiyaz Khan, Tom Schaul
2019	A*	`conf`	Approximate Inference Turns Deep Networks into Gaussian Processes. NeurIPS Mohammad Emtiyaz Khan, Alexander Immer, Ehsan Abedi, Maciej Korzepa
2019	J	`jnl`	Approximate Inference Turns Deep Networks into Gaussian Processes. CoRR Mohammad Emtiyaz Khan, Alexander Immer, Ehsan Abedi, Maciej Korzepa
2019	A*	`conf`	Fast and Simple Natural-Gradient Variational Inference with Mixture of Exponential-family Approximations. ICML Wu Lin, Mohammad Emtiyaz Khan, Mark Schmidt
2019	J	`jnl`	Fast and Simple Natural-Gradient Variational Inference with Mixture of Exponential-family Approximations. CoRR Wu Lin, Mohammad Emtiyaz Khan, Mark Schmidt
2019	A*	`conf`	Practical Deep Learning with Bayesian Principles. NeurIPS Kazuki Osawa, Siddharth Swaroop, Mohammad Emtiyaz Khan, Anirudh Jain, Runa Eschenhagen, Richard E. Turner, Rio Yokota
2019	J	`jnl`	Practical Deep Learning with Bayesian Principles. CoRR Kazuki Osawa, Siddharth Swaroop, Anirudh Jain, Runa Eschenhagen, Richard E. Turner, Rio Yokota, Mohammad Emtiyaz Khan
2019	A*	`conf`	Scalable Training of Inference Networks for Gaussian-Process Models. ICML Jiaxin Shi, Mohammad Emtiyaz Khan, Jun Zhu
2019	J	`jnl`	Scalable Training of Inference Networks for Gaussian-Process Models. CoRR Jiaxin Shi, Mohammad Emtiyaz Khan, Jun Zhu
2019	J	`jnl`	Stein's Lemma for the Reparameterization Trick with Exponential Family Mixtures. CoRR Wu Lin, Mohammad Emtiyaz Khan, Mark Schmidt
2019	J	`jnl`	TD-regularized actor-critic methods. Mach. Learn. Simone Parisi, Voot Tangkaratt, Jan Peters, Mohammad Emtiyaz Khan
2019	J	`jnl`	VILD: Variational Imitation Learning with Diverse-quality Demonstrations. CoRR Voot Tangkaratt, Bo Han, Mohammad Emtiyaz Khan, Masashi Sugiyama
2018	A	`conf`	Bayesian Nonparametric Poisson-Process Allocation for Time-Sequence Modeling. AISTATS Hongyi Ding, Mohammad Emtiyaz Khan, Issei Sato, Masashi Sugiyama
2018	A*	`conf`	Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam. ICML Mohammad Emtiyaz Khan, Didrik Nielsen, Voot Tangkaratt, Wu Lin, Yarin Gal, Akash Srivastava
2018	J	`jnl`	Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam. CoRR Mohammad Emtiyaz Khan, Didrik Nielsen, Voot Tangkaratt, Wu Lin, Yarin Gal, Akash Srivastava
2018	C	`conf`	Fast yet Simple Natural-Gradient Descent for Variational Inference in Complex Models. ISITA Mohammad Emtiyaz Khan, Didrik Nielsen
2018	J	`jnl`	Fast yet Simple Natural-Gradient Descent for Variational Inference in Complex Models. CoRR Mohammad Emtiyaz Khan, Didrik Nielsen
2018	J	`jnl`	Low-Rank Tensor Decomposition via Multiple Reshaping and Reordering Operations. CoRR Chao Li, Mohammad Emtiyaz Khan, Shengli Xie, Qibin Zhao
2018	A*	`conf`	SLANG: Fast Structured Covariance Approximations for Bayesian Deep Learning with Natural Gradient. NeurIPS Aaron Mishkin, Frederik Kunstner, Didrik Nielsen, Mark Schmidt, Mohammad Emtiyaz Khan
2018	J	`jnl`	SLANG: Fast Structured Covariance Approximations for Bayesian Deep Learning with Natural Gradient. CoRR Aaron Mishkin, Frederik Kunstner, Didrik Nielsen, Mark Schmidt, Mohammad Emtiyaz Khan
2018	J	`jnl`	TD-Regularized Actor-Critic Methods. CoRR Simone Parisi, Voot Tangkaratt, Jan Peters, Mohammad Emtiyaz Khan
2018	—	`conf`	Variational Message Passing with Structured Inference Networks. ICLR (Poster) Wu Lin, Nicolas Hubacher, Mohammad Emtiyaz Khan
2017	J	`jnl`	Conjugate-Computation Variational Inference : Converting Variational Inference in Non-Conjugate Models to Inferences in Conjugate Models. CoRR Mohammad Emtiyaz Khan, Wu Lin
2017	A	`conf`	Conjugate-Computation Variational Inference: Converting Variational Inference in Non-Conjugate Models to Inferences in Conjugate Models. AISTATS Mohammad Emtiyaz Khan, Wu Lin
2017	A*	`conf`	SmarPer: Context-Aware and Automatic Runtime-Permissions for Mobile Devices. IEEE Symposium on Security and Privacy Katarzyna Olejnik, Italo Dacosta, Joana Soares Machado, Kévin Huguenin, Mohammad Emtiyaz Khan, Jean-Pierre Hubaux
2017	J	`jnl`	Variational Adaptive-Newton Method for Explorative Learning. CoRR Mohammad Emtiyaz Khan, Wu Lin, Voot Tangkaratt, Zuozhu Liu, Didrik Nielsen
2017	J	`jnl`	Vprop: Variational Inference using RMSprop. CoRR Mohammad Emtiyaz Khan, Zuozhu Liu, Voot Tangkaratt, Yarin Gal
2016	A	`conf`	Faster Stochastic Variational Inference using Proximal-Gradient Methods with General Divergence Functions. UAI Mohammad Emtiyaz Khan, Reza Babanezhad, Wu Lin, Mark Schmidt, Masashi Sugiyama
2016	B	`conf`	Online Collaborative Prediction of Regional Vote Results. DSAA Vincent Etter, Mohammad Emtiyaz Khan, Matthias Grossglauser, Patrick Thiran
2015	J	`jnl`	Convergence of Proximal-Gradient Stochastic Variational Inference under Non-Decreasing Step-Size Sequence. CoRR Mohammad Emtiyaz Khan, Reza Babanezhad, Wu Lin, Mark Schmidt, Masashi Sugiyama
2015	J	`jnl`	UAVs using Bayesian Optimization to Locate WiFi Devices. CoRR Mattia Carpin, Stefano Rosati, Mohammad Emtiyaz Khan, Bixio Rimoldi
2014	A	`conf`	Scalable Collaborative Bayesian Preference Learning. AISTATS Mohammad Emtiyaz Khan, Young-Jun Ko, Matthias W. Seeger
2014	C	`conf`	Variational Gaussian Inference for Bilinear Models of Count Data. ACML Young-Jun Ko, Mohammad Emtiyaz Khan
2013	—	`conf`	Fast Dual Variational Inference for Non-Conjugate Latent Gaussian Models. ICML (3) Mohammad Emtiyaz Khan, Aleksandr Y. Aravkin, Michael P. Friedlander, Matthias W. Seeger
2012	A	`conf`	A Stick-Breaking Likelihood for Categorical Data Analysis with Latent Gaussian Models. AISTATS Mohammad Emtiyaz Khan, Shakir Mohamed, Benjamin M. Marlin, Kevin P. Murphy
2012	—	`conf`	Fast Bayesian Inference for Non-Conjugate Gaussian Process Regression. NIPS Mohammad Emtiyaz Khan, Shakir Mohamed, Kevin P. Murphy
2011	A*	`conf`	Piecewise Bounds for Estimating Bernoulli-Logistic Latent Gaussian Models. ICML Benjamin M. Marlin, Mohammad Emtiyaz Khan, Kevin P. Murphy
2010	—	`conf`	Variational bounds for mixed-data factor analysis. NIPS Mohammad Emtiyaz Khan, Benjamin M. Marlin, Guillaume Bouchard, Kevin P. Murphy
2009	—	`conf`	Accelerating Bayesian Structural Inference for Non-Decomposable Gaussian Graphical Models. NIPS Baback Moghaddam, Benjamin M. Marlin, Mohammad Emtiyaz Khan, Kevin P. Murphy
2007	J	`jnl`	An Expectation-Maximization Algorithm Based Kalman Smoother Approach for Event-Related Desynchronization (ERD) Estimation from EEG. IEEE Trans. Biomed. Eng. Mohammad Emtiyaz Khan, Deshpande Narayan Dutt
2004	—	`conf`	Expectation-maximization (EM) algorithm for instantaneous frequency estimation with Kalman smoother. EUSIPCO Mohammad Emtiyaz Khan, D. Narayana Dutt